Every 2-3 years, I manage to wear out a keyboard. With nearly 3000 articles written for my CNCCookbook blog alone, 5 other blogs, and countless emails responded to, I guess that goes with the territory.

Normally, I don’t think too much about what keyboard to buy, I just head over to Staples and get whatever they have. This time I decided to order online, and while I was at it, I checked around for some reviews. Was there some ultimate keyboard that wasn’t too expensive I could try?

It turns out there is an ultimate keyboard, and if your day involves lots of typing, you need to check one out. I hate to be suspenseful, but I put a whole keyboard review over on CNCCookbook, and even with this premium keyboard, I’m not going to retype it all again here.

Click the link, head over, and check it out.

]]>https://smoothspan.wordpress.com/2016/10/11/worlds-best-pc-keyboard/feed/0Bob Warfieldtype-heavenReflections on Six Years of Content Marketing in a Bootstrapped Startuphttps://smoothspan.wordpress.com/2016/09/06/reflections-on-six-years-of-content-marketing-in-a-bootstrapped-startup/
https://smoothspan.wordpress.com/2016/09/06/reflections-on-six-years-of-content-marketing-in-a-bootstrapped-startup/#commentsTue, 06 Sep 2016 15:22:55 +0000http://smoothspan.wordpress.com/?p=3085]]>

All told, it took almost two months of part-time effort and was as much work and words as a small novella. I don’t expect to win any literary prizes with it, but I do expect it to help a good many CNC (Computer Numeric Control, the field my business, CNCCookbook, is serving) Beginners to launch their journey into the world of Robotic Machine Tools that make things for you.

Writing the article has left me feeling reflective about the CNCCookbook journey. It’s become one of the biggest if not the biggest CNC-related blog on the Internet. I’ve accomplished marketing goals all by myself that a lot of top marketing people would love to recreate.

CNCCookbook has been a magic business for me in the magical world of CNC. We live in an age of 3D Printing, which gets most of the Hype, but also of CNC in general. Computer-controlled machine tools that are even more sophisticated than those that put Men on the Moon are available not just to businesses, but also to hobbyists and small businesses operating out of their garages.

I recently interviewed Zach Kaplan, the founder of Inventables, for the CNCCookbook blog. In the inverview, Zach remarks that there are some 300,000 manufacturers in the US today, but he thinks within 10 years there will be over 3 million manufacturers. This amazing growth will be fueled by the power of these entry-level CNC machines such as the X-Carve CNC Router that Zach’s company, Inventables, sells.

I think Kaplan is probably conservative, and that we’ll get to that 3 million manufacturer mark much sooner than 10 years. We live in an unprecedented time of opportunity with desktop CNC to help us make products and the Internet to help us market them.

I’ve interviewed many small CNC businesses that got started from nothing and are doing very well. A great example would be the little Iowa company of one Brad Martin that makes bottle openers in the shape of grenades. It’s called Tactical Keychains and affords Martin a nice living where he is growing steadily and is his own boss.

X-Carve is VC-Funded, while its chief competitor, Carbide3D (another outfit I’ve interviewed from time to time) was crowdfunded via Kickstarter. My own company, CNCCookbook, was created with no external capital, just my own sweat equity. Those are really the rungs on the evolutionary funding ladder–VC, Crowdfunding, and now Bootstrapping.

Personally, I think 4 years is a pretty small price to pay for the lower risk and superior economics that are possible when you bootstrap. I’ve had plenty of experience with Venture Money–CNCCookbook is my 8th Startup and VC’s were involved with the other 7. I wish I’d embarked on CNCCookbook and the Boostrapping path 10 years ago. I’d be that much further ahead on a journey that looks like it has no ceiling.

Today, I take home more cash than I have taken home from any of the VC companies. That doesn’t count stock option money, but it’s still pretty darned good when you consider I’ve been an executive for two companies that made it to pretty decent sized public firms. I was able to do this all by myself–I have a few part-time employees, but have gotten here largely through my own efforts.

I owe my success to my ability to write software, but just as much if not more to my ability to do Content Marketing. It’s been my magic bullet, and it works something like this:

I give away valuable content about CNC, the market I’ve chosen to be in.

People find the content via Social Media, Search Engines, and Referrals as other sites link to CNCCookbook.

They visit, consume the content, enjoy it, and pass on the word. I can’t claim it’s viral, but it’s pretty darned good.

As they become regular readers, they’re exposed to content about the kinds of CNC problems my software solves. It’s fairly low-key, and I try to avoid ever being spammy. Eventually, those customers that have the same problems take a free trial of our software. If they like it, they buy it, and I get to repeat the cycle for others.

If you’re wondering about the details of all that, I haven’t written about it much, although I mean to at some point. For now, the best you can do is visit another of my web sites, which I call Firehose Press.

Firehose Press is an odd site. It’s a blog where I haven’t written a single word of the content. That’s right–not a single word. Instead, it contains clippings from every marketing article I’ve ever read that influenced me on my CNCCookbook journey. Y ou’ll see there’s a lot of them. But, it’s your opportunity to take a personally curated tour that will let you follow in my footsteps. I’ve distilled out the best material for you.

Give Firehose Press a casual browse. If you’re interested in how to market a Startup Business, you will almost certainly find something valuable there. After all, it’s from some of the best minds in marketing.

His conclusion is, “No,” largely because he makes the case that you won’t make nearly as much money. His concerns are:

You don’t vest much. He estimates 15% a year allowing for future grants.

You may not be able to afford to buy the shares when you leave if the strike price is too high.

If you get RSUs instead of options, you may get nothing when you leave.

I’ll address #1 in a minute, but let’s talk about #2 and #3.

Not being able to afford to buy the shares implies you’re joining the startup relatively late. The average startup requires 7 years start to finish to reach liquidity. How late does the startup have to be before you can’t afford to buy your shares? Tough to say. An early unicorn would certainly do it. But in most cases, my guess is you’re at least halfway through the 7 years. So you can no longer buy shares at say the 3 year mark.

Okay, but is that a problem if you join at year 3 and allocate 2 years to figure out whether it is worth staying the remaining 2? Unless things are still seriously hot after your 2 years are up (year 5), it seems to me you can still look at it as a 2 year stint and maybe just buy fewer shares. If the thing really is a Unicorn, you’ll need fewer. In other words, reason #2 is not as compelling as it seems–you don’t have to settle for nothing, you will get a chance to look at a few more cards in the poker hand during the 2 years, and you may simply wind up with a smaller return if you mistakenly leave early because you didn’t buy all of your vested shares.

Issue #3 I look at totally differently. Do you want to join a startup that offers RSU’s (Restricted Stock Units) instead of a options? Do you want to join a startup that gives you nothing if you leave after having given them 2 years? Personally, I just wouldn’t sit down to play at such a table. The house has things rigged too thoroughly in their favor. I’m sure there are endless anecdotes about companies with RSU’s that made fortunes for their employees, but remember-the odds are already heavily stacked against you (shortly we’ll see just how much). Do you really want this additionally risk? And are companies that operate this way more or less successful? Are they more or less likely to be good to their employees, people like you? Color me skeptical.

Now let’s get back to concern #1–“You didn’t vest enough to make real money.” You only got 15% of what you could’ve gotten instead of 100%. Let’s look at it somewhat differently. First, your resume looks terrible if you have a new job every year, so you need to stay for 2 years, not 1. That gets you 30% rather than 15%, a big step up.

Second, concern #1 is expressed as though making the money is a sure thing, and it most certainly is not. I prefer to look at it this way:

Should you take one 8-year job or four 2-year jobs? Which one has the highest likelihood of putting you in the money?

If we look at it that way, and make a few assumptions, it’s possible to model the two scenarios in Excel. In fact, we can handily run a Monte Carlo simulation and see what results we get.

Here are the assumptions I used for the simulation:

– You can either stay in 1 job for 8 years (about what it takes to go from 0 to liquidity in round numbers) or you can take 4 jobs and stay 2 years each.

– Your chance of picking a winner is 1/8. 1 in 8 deals wins. Overall 3 out of 4 VC deals fail to return the investor’s money. It’s a sure bet that a fair number that return the money still won’t return anything to you as the VC’s have all sorts of preferential terms in the deal. So let’s just say it is 1 in 8.

– If the 1 job guy gets a win, he gets 100%. If the 4 job guy gets a win, he gets 30% (2 years at Jason Lemkin’s 15% a year figure).

Now we do 5000 iterations of that in an Excel spreadsheet for a Monte Carlo simulation. Here are the results:

– The 1 job guy only has a 14% chance of getting his 100% of shares to return. I wonder how many would sign up for a startup if they soberly concluded those were the odds?

– The 4 job guy has a 42% chance of getting his 30% of shares in the money.

Whoa!

Way better odds for the portfolio effect of taking 4 jobs with 2-year stints. So now the decision is a utility curve issue. Say we’re talking $10 million. Do you want a 14% chance at $10 million or a 42% chance at $3.3 million?

I’m not even sure that’s the right strategy, it is again, a utility curve thing. What’s your goal? How much will you sacrifice to get to that goal? How much is enough money?

How lucky do you feel?

Or, look at it this way:

You only have so many deals, so many throws of the dice, in your entire career. How many are left, particularly when you consider that many feel startups are a young person’s game?

I don’t feel startups have to be a young person’s game, BTW, but I do think you have to find some way of achieving a portfolio effect to maximize your likelihood of success. Otherwise, you’re working your tail off and taking substandard pay mostly to help your investor’s win big due to their portfolio effect while the greatest likelihood is you’ll make absolutely nothing.

PS: Now you’re wonder if your odds will be better because you’re smarter and this deal you’re looking at is just so good. Let’s say your odds are the same as the VC’s–1 in 4 deals will hit instead of 1 in 8.

What does doubling the odds do for you in the Monte Carlo simulation?

Recall we originally had a 14% chance of making 100% and a 42% chance of making 33%. If we double the odds per deal, we now have a 26% chance of making 100% and a 69% chance of making 33%.

I don’t know about you, but having the odds favor me on each 2 year stint to the tune of 69% sounds awesome. Heck, I might even succeed at more than one of the 4 stints, which would get my 33% up to 66% or maybe even more.

]]>https://smoothspan.wordpress.com/2016/07/09/the-economics-of-vc-startups-for-individuals/feed/1Bob WarfieldHuhroll-the-diceA/B Testing is a Great Idea for SaaS Startupshttps://smoothspan.wordpress.com/2016/05/19/ab-testing-is-a-great-idea-for-saas-startups/
https://smoothspan.wordpress.com/2016/05/19/ab-testing-is-a-great-idea-for-saas-startups/#respondThu, 19 May 2016 14:05:29 +0000http://smoothspan.wordpress.com/?p=2973]]>Tomasz Tunguz (Redpoint VC) and Lloyd Tabb have got it wrong–way wrong. Tunguz recently published an article based on a conversation he’d had with Tabb that suggests early and mid-stage software companies can’t benefit from A/B Testing because they don’t see enough web traffic to make the results statistically significant. They suggest that instead, they should make decisions based on qualitative data:

… interviewing users about the whys underpinning their points of view on price, reviewing the video of people exploring the product, and opinions about design. It’s the qualitative data, the acumen of an brilliant designer, the insight of a skilled product manager, the empathy of a master marketer.

Ouch! Back to anecdotal evidence and marketing decision making by the most important person in the room. Back to the bad old days, in other words. There’s nothing wrong with doing those things they suggest, but before you bet your company on the results, you must A/B test them. These are just inputs to decide what to test, in other words.

Back to anecdotal evidence and the bad old ways of marketing…

Before we throw the AB Testing baby out with the bathwater, let’s take a closer look at what’s possible. The Chief Witness for Tunguz and Tabb is Optimizely’s Sample Size Calculator:

It’s a great tool that I use all the time, BTW. They’ve selected the default view, which suggests that if you have a baseline conversion rate of 3%, and you want to see a minimum 20% detectable effect with 90% confidence, you will need 12,000 visitors to the page.

There are two key questions to explore before we can agree or disagree with the proposition in an informed manner:

Are these the right inputs for Sample Size Calculator?

Given the right inputs, is the sample size too large for most startups to attain?

For the first question, I submit that the defaults are actually not very relevant at all. Requiring 90% confidence or be willing to accept anecdotal evidence is pretty silly.

Heck, I run my own bootstrapped startup, it’s entirely my capital that’s at risk (I’ve accepted no outside investment), and I would be thrilled to ring up 70% confidence interval tests all day long.

As it turns out, Optimizely will only let us go to 80% confidence, but Google’s A/B Testing will tell us it’s evaluation of the confidence regardless of level. I will add that the statistical confidence is also not the only factor we should consider. It’s important to make sure you really have a representative sample. For example, test results may vary by day of the week, so I never accept a test that’s run for less than a week, even if the confidence is 90% or more. In fact, I typically prefer 2 weeks as a minimum.

If we plug in an 8% conversion at 80% confidence, the sample size plummets to 3,300 visitors before we can measure a 20% detectable effect. We’ve cut it almost 4x, but we’re not quite done. What about that 20%? Is it not worth conducting A/B tests unless they result in 20% differences?

Here I’ll turn to my own experience AB Testing for my own company, CNCCookbook. In the last 8 months I’ve conducted 55 A/B Tests. The average change between the baseline and the variant I measured was 30%. Are you surprised? I was VERY surprised at how much impact even seemingly little things could have. FWIW, 44% of my tests yielded a positive improvement, 29% showed the idea failed, and 49% of the tests failed to reach statistical significance. I have no idea how that compares to the scores for other marketers, but I am very happy with the results.

If we plug that 30% number in, we get to a sample size of 1,300 visitors. Applying my rule that I usually test for 2 weeks, we need to come up with less than 100 visits a day to the web page we’re testing.

Is that bar too high for startups to clear? It shouldn’t be if the marketers are doing their job right. I’m a one-man bootstrapped company and my CNCCookbook site sees about 15,000 views a day to the site. I get about 250 a day to the home page and about 450 a day to my product home page. As I write this, Google Real Time Analytics cheerfully informs me there are about 50 people running around on my site.

Clearly I can do very statistically significant A/B Testing and it has benefited me quite a lot. I get over 6000 visits in 2 weeks so I can measure as little as a 15% change in that time, and even less if I am willing to let the tests run longer. Incidentally, don’t overlook the value of a test that ISN’T significant. That test is telling you at the very least that even if it is bad, it is no worse than the statistically measurable results. So, if we can test to a 20% detectable effect, adopting the wrong variant will do no more harm than 20%. Sometimes when we need to move ahead boldly, knowing we can do no more harm than that is good enough.

Granted, I’ve had this company for a few years, but if I can get this far by myself, a VC-funded startup should be able to do at least as well and much faster. They have to in order to have much hope for a Unicorn-valuation. Tabb’s company, Looker, the one that presumably prompted the discussion, looks like it should have a little less than half the organic search traffic I get based on SEMRush results. Clearly, Looker should be able to benefit tremendously from A/B Testing if it chooses to.

So, VC Board Members–expect quantifiable results from your portfolio companies and don’t take sample size whining for an answer. Entrepreneurs, saddle up and ride this A/B Testing horse–it’s a powerful tool that can really move the needle.

My best advice for startups right at the beginning, BTW, is start building your audience BEFORE you build your product. I call it achieving Content-Audience fit, I’ve been writing about it for years, and it is absolutely the very first thing a founding team should do when they get together. Achieving it provides a number of powerful validations for your team, but more importantly, it validates there is a reachable audience, and in reaching it, you gain a powerful tool for shaping your journey to Product-Market Fit. Not to mention, you set yourself up to achieve enough traffic to do meaningful A/B Testing just that much sooner.

Stealth Mode is harmful in this respect–it delays your access to Content-Audience fit for no meaningful benefit. So what if the world knows what broad market you’re working in or even what broad problems you write about? You don’t have to tell them anything about your product or how it helps solve those problems.

No more excuses–get on with your marketing people, and do some rigorous AB Testing of it!

]]>https://smoothspan.wordpress.com/2016/05/19/ab-testing-is-a-great-idea-for-saas-startups/feed/0Bob WarfieldPickardFacePalmoptimizely_sample_sizeWhat Really Caused Our Manufacturing Jobs to Move to China?https://smoothspan.wordpress.com/2016/04/28/what-really-caused-our-manufacturing-jobs-to-move-to-china/
https://smoothspan.wordpress.com/2016/04/28/what-really-caused-our-manufacturing-jobs-to-move-to-china/#respondThu, 28 Apr 2016 21:34:24 +0000http://smoothspan.wordpress.com/?p=2955]]>Every now and again, a good rant can be cleansing. I mean that in the best possible way.

Fred’s not long enough on facts to do much more than be troubled and hand wave away the discussion. In his mind, there won’t be any manufacturing jobs because automation is destroying them so quickly anyway.

It’s really the Robots that took all the jobs…

Fred doesn’t think it’s worth bothering with the Manufacturing Sector because soon there won’t be any jobs left after automation anyway. Far better to make everyone an IT guy or some such. We’re in a transition we should double down on be happy with. Something like what he says here:

The US and a number of other countries around the world are building new information based economies. That is the long term winning strategy.

So while we can critique our leaders (business and political) for giving up on the manufacturing sector a bit too early, I think the US has largely played this game correctly and will be much better off than the parts of the world that have taken the low cost manufacturing jobs from us.

The thing is, most all of this is a lot of Lies, Half Truths, Myths, and general Bollocks that got started by people who would benefit from offshoring manufacturing and is maintained as a cherished belief as so many myths are just because it’s been a self-fulfilling prophecy. In other words, if we destroyed our manufacturing economy it must be because our manufacturing economy was doomed and not worth saving in the first place.

Take the Robot argument. It’s uber-popular in VC circles because people like Andrew McAfee have made careers out of pushing this thesis. Yet, if we actually look at the numbers (which I do in detail in the article below), it’s very hard to make the case that Robots have taken more than maybe 20% of the jobs away. That’s a far cry from eliminating an entire market segment or deciding they’ll never be able to produce enough jobs to be worth considering.

The reality is the whole thing was manipulated by a variety of parties, is based on a large number of non-truths, and is relatively easy to reverse. Moreover, it would be extremely valuable to reverse it.

I just read a post on the KissMetrics Blog by Cody Lister entitled, “More Trial Users is Not the Answer For Your Startup’s Growth.” It’s not a terrible post. In fact, some aspects are pretty decent. Lister basically wants startups to focus on better engagement and the onboarding experience and less on just running as many people as possible through the trial process. He wants you to be sure you’ve got product market fit before you try to scale out with as many trials as possible. I have no problem with the latter, BTW, but it is unrelated to the areas I do have a problem with.

Unfortunately, perhaps due to the act of trying to make the point as persuasively as possible, he strays into at least one area where I think his advice is dead wrong. It’s way too Black and White, and whenever someone gives me a Black and White answer, I instinctively look for the exceptions to the rule. Let’s put aside that in fact more free trials will help you to grow, it simply may not be the optimal thing for you to be focused on right now (or it may be, it all depends).

Instead, let’s drill down on the area that really got me thinking it was bad advice from a marketer who should know better. Lister states:

Eliminate Or Reduce Free Trials

What if one day, your team just decided to shut down your free trial accounts that were past 14 days since their sign up date? Would you suddenly go out of business?

No, you’d save money from server costs and force people to make a decision.

It’s only when your free trials run out that you know whether the end user found your product worth paying for.

You need to figure out how to improve the engagement of your existing trial users to convert them to paid users.

ConvertKit and Edgar, which today generate millions of ARR, never offered free trials.

I often come across startups that give away free trials for 30 to 60 days. I just don’t get it.

I could not disagree more with his advice to eliminate or limit free trials to 14-days. He states it as an absolute to the point that, “he just doesn’t get” why anyone would be stupid enough to offer a 30 or 60 day trial.

He gives only two odd exceptions to his rule:

A B2B SaaS offering costing more than $200 a month. No explanation whatsoever why the arbitrary figure of $200 was chosen.

An offering where personal data had to be entered and value received increases proportionally to the amount of data entered. He argues this creates switching costs, which is worthwhile, but actually misses the point. What he misses is not only does it create switching costs, but the more data in services like DropBox, the more likely the user is to experience the “Aha” moment that closes the sale. Switching costs come later, after the user is satisfied and someone else wants to woo them away.

Let’s dig into it with a couple of real world examples that I think will help explain the real reasons why you need to think about your Free Trial in terms of the user experience and not in terms of arbitrary advice from marketers.

Ironically, one of the reasons I tried but did not adopt KissMetrics (the very blog where this is posted) was because I could not tell within 14 days whether it would deliver value. In fact, KissMetrics is a wonderful illustration of the problem with this one-size-fits-all advice.

It’s biggest benefit is a better understanding of your sales funnel. So ask yourself, “How far does a user travel in the funnel in 14 days?” Further, how much of the 14 days is needed to get things set up and to accumulate enough people travelling through the funnel to make things even interesting?

You can now see where I’m going. It might very easily take more than 14 days to get to that “Aha” moment where I see the value in a product like KissMetrics and I’m ready to pay up for it. In fact, for my company, it really was longer than 14 days. This was exacerbated by various aspects of the KissMetrics user experience. It took the service time to accumulate enough data points to show me any funnel reports. It took me time to understand the service well enough to get my funnels set up properly. And it took time given my web site’s traffic to accumulate enough data points to see any kind of picture clearly. BTW, it’s no small web site, I get 2 million uniques a year. Pretty good for a small business.

I believe 30 days would’ve worked nicely for my case, but alas, I only had a 14-day trial to work with. So I moved on.

Develop a new lead nurturing automation campaign far enough to evaluate the product

I felt it was reasonable that my “Aha” moments for Drip would include:

Verifying it could do what my existing provider, Mailchimp, was already doing for my business.

Verify that it could so something that Mailchimp couldn’t via its increased automation features. After all, Drip was going to be more expensive–it should show me some magic relative to Mailchimp during the trial.

As I documented in my write up, I was unable to accomplish these tasks within 14-days despite trying like crazy to get them done. I had a mixture of problems ranging from product bugs to unclear UX to my own stupid noobie user mistakes. I could not even get my email newsletter out, despite trying hard for 2 weeks running, so I couldn’t even verify Drip worked as well as Mailchimp, let alone see the impact of its new features.

I wound up sending Drip’s Founder an offer–extend the free trial and work with me until we can make my Drip experience a happy one. In exchange, I’d buy the product and write about my experiences in places like this blog. He declined, saying many of his competitors didn’t offer a free trial at all.

Here’s the thing:

If you’re going to offer a free trial, you really should make sure it is long enough that your users can reach the “Aha” moment where they’ve confidently demonstrated your product’s value and it’s an easy choice to reach into the pocketbook and become a paying customer. Ignore all the other rules of them because reaching the “Aha” moment is the only thing that matters for your Free Trial. That is its singular purpose.

If you’re not going to do that, why have a free trial at all? I can’t imagine a reason unless it’s just part of the old bait and switch–get them to commit a little, even just give us their email, and each thing they give up will make the next thing that much easier. That’s a well-understood marketing concept, and it even works to an extent, but is that really the way to build your successful business?

I can’t believe marketers think so, at least not the good marketers. Please tell me you’re not in that camp.

Length of trial is something that should be tested, preferably AB tested if you can arrange it. Don’t get too greedy and eliminate your trials before your customers can experience the “Aha” moment that guarantees they will love the product. If you can make that happen in 14 days, great, but don’t just assume that’s the case. Give them whatever time they need. Even offer to extend the free trial for ANOTHER 30 days if they’re not done evaluating.

You’d be surprised what treating your customers as human beings rather than inventory will do for you.

]]>https://smoothspan.wordpress.com/2016/02/18/bad-advice-on-free-trials-from-marketers-who-should-know-better/feed/0Bob Warfield262_1Drip: Great Idea, Not Ready for Prime Timehttps://smoothspan.wordpress.com/2016/02/05/drip-great-idea-not-ready-for-prime-time/
https://smoothspan.wordpress.com/2016/02/05/drip-great-idea-not-ready-for-prime-time/#commentsFri, 05 Feb 2016 19:13:25 +0000http://smoothspan.wordpress.com/?p=2823]]>As I’ve written recently, I’ve had some problems with my Email provider Mailchimp. I use Mailchimp to do a variety of emailings as part of my software company, CNCCookbook. We’re a bootstrapped company that makes software for CNC Manufacturing, and we’ve managed to do very well largely using Content or Inbound marketing. The company is completely bootstrapped, yet we have traffic that makes us the largest CNC-related Blog and Content resource on the Internet.

The problems with Mailchimp were not life-threatening. Basically, they were getting some links wrong in the Plain Text version of my RSS Newsletter. They have been quick to follow up, comping me with some free months and promising to get the problems fixed. There’s a reason they’re as large as they are and they know how to handle customers.

The thing is, I’ve wanted to move up to a more powerful Marketing Automation solution. To do so, I needed features that were missing from Mailchimp and that it doesn’t look to me like they will be adding very soon. In essence, they boil down to more powerful Workflows that let me do highly personalized Lead Nurturing. I believe Lead Nurturing is the next step in getting the maximum value out of my large mailing list (nearly 50,000 members).

So I took this as an opportunity to try another vendor, and I settled on Drip. The information on their web site made it look like they had the functionality I needed and I had seen that some of the sites I value for marketing information were using Drip. The price was reasonable for a company like mine–a bit more than Mailchimp but bringing more functionality. Best of all, I really felt their marketing slogan was perfect for my needs:

Lightweight Marketing Automation That Doesn’t Suck

Unfortunately, despite a week of working hard with Drip, it became clear that it just wasn’t ready for Prime Time. At least not for a firm the size of CNCCookbook (which doesn’t seem all that large to me being bootstrapped by one guy who is an engineer and not a Marketing Guy).

Let me describe what I was trying to do and what problems I encountered so that others may understand. By all means, if you’re aware of a solution that can deal with these things without breaking my bank, let me know about that too. The Marketo’s, Eloqua’s, and Pardot’s in the world can probably do it with ease, but they’re far too expensive. Even Infusionsoft looks extremely expensive to me.

Step 1: An RSS Email Newsletter

CNCCookbook has grown through content marketing and I put out 3-5 new articles every week on our blog. I build the mailing list for that blog via various forms and popups on the web site coupled with premium content offers for signing up. One of the reasons I picked Mailchimp at the time was that it made it extremely easy to automate a newsletter with an RSS feed, and one of the reasons I picked Drip is that it clearly advertised the same capability.

Drip does a lot of things with their RSS (and other email workflows) that I love:

With one click you can specify to do a follow-up remailing to those who didn’t open the first one. This is hugely valuable all by itself.

Their email creation UI is fully on part with Mailchimp’s and even a bit cleaner and easier to use.

But, there were problems–some major, some minor, all added up to my not getting a single Email Newsletter out before I decided to cancel my trial after a little over a week of intensive effort. Here’s what I found:

You have to request the RSS Feed feature be turned on. I found this to be odd and off-putting. It’s like they’re not very proud of it or something.

It does show up in the UI looking like something of an after thought.

There’s no way to do Mailchimp’s useful “Forward to a Friend” link.

You can’t customize the Subscription Management page.

You can’t manually control whether a user gets the HTML or Plaintext version. In fact, I don’t think you have a way to even tell which one a given user has chosen though the UI shows both.

I was never able to successful send myself a Plain Text version so I could verify it was good to go.

Importing my Mailchimp list took hours. Makes me wonder just how scalable this SaaS app is in an age of Cloud Scalability.

That was all stuff I got my head around and was willing to move forward with. But then there were some major gotchas. For example, you can set the RSS up to generate the bulk mailing but wait for you to approve it before it goes out. You can even trigger its generation without waiting for the once a week date so you can use it to debug your efforts.

Bravo, very cool feature!

But the bad news is, each time you trigger it, it won’t run again until the specified interval. So, if you test it, but don’t send the mails, you can’t do it again for real for 1 week. Whoa, totally unworkable and the reason I never sent one email newsletter.

Lead Nurturing and Fancy Workflows

This is where the product really shows promise. On paper, at least, it is capable of much Marketing Automation Coolness. Want to trigger actions based on what people are doing on your site? This is the Holy Grail of email personalization, and Drip can do that. You drop a little Javascript snippet on every page and voila! They are now monitoring all that activity. You can even bring up a subscriber and see the activity. Tres Cool!

Want to know if they opened emails or clicked through? No worries. There’s even a lead scoring mechanism. Oh boys! Now you’re ready to put together some awesome Lead Nurturing Workflows, right?

Well, not so fast. Let me describe the very basic lead nurturing program I came up with, and my attempts to implement it. Here is the basic Lead Funnel I was after:

No Rocket Science, right? The Brand Loyalty stage is about our giving value in the initial emails by sharing our most popular and valuable articles. Gradually, we start to introduce some popular articles that are about the sorts of problems our software addresses. Then we provide articles that show how our software solves the problems. Finally, we provide articles that show why we are the best choice.

What we want to use the workflow in a product like Drip to do is to determine which articles are being read. Based on that, we may escalate or fall back from one stage in the funnel to another:

Based on which email links readers click, we may escalate them to later funnel stages. If they quit clicking or opening emails, we drop back and start over because they’re not ready…

Again, this is pretty basic lead nurturing, so I’d expect most products to be able to handle this kind of thing. Here are the obstacles I encountered with Drip:

Inability to work with large numbers of links in Visual Workflows. For example, they’re very excited about their new Visual Workflow Editing. It looks awesome in the demo, but for even middling complex workflows it is very cumbersome. For example, you can’t horizontally scroll the diagrams. I was stretching the window across 2 32″ monitors but still lost the ability to edit when I wanted rules based on 5 links.

You can use their Rule Editor, but it is going to be a lot of work. What would be ideal would be to simply enter a list of links that trigger a new campaign, with one campaign assigned to each funnel level.

There’s one single lead score and one threshold for everything. I need separate funnels, campaigns, and lead scores for each product. I want to potentially trigger transition to another level of the funnel not just on links clicked but on leadscore. Maybe a score of 25 = Awareness, 50 = Consideration, and 75 = Decision, or some such. Not possible–Drip’s Lead Scoring is way too embryonic. It would also be nice to be able to reset or reduce the lead score if the prospect fails to move forward and we fall back to wait for another time.

There were a number of other detail level fit and finish issues, but I tend to overlook those if a company is moving at a good clip and working with me. Speaking of working with me, I will say that Drip has some of the best Customer Service I’ve yet come across.

What Now?

I really wanted to work with these guys, their product has a lot of promise. But I had so many problems during the 21 day trial it was clear I wasn’t going to get it figured out. So I sent the founder a proposal. If he’d comp me a quarter and work with me on the issues, I’d work with him. I’d write about his product, serve as a case study, and provide him with input. In the end, I’d be a decent sized account for him too as we’re off the top of his published plans.

I was surprised when he turned me down:

Hi Bob,

Thank you for taking the time to put your thoughts down and let us know your situation. I’m sure it’s been frustrating so far as you’ve attempted to get setup, and I appreciate you touching base about this.

From your email, it sounds like a tool like MailChimp, AWeber, or ConvertKit is actually going to be your best bet. It seems that Drip isn’t a fit for what you’re looking to do based on the number of issues you’ve faced. We are unable to extend trials past 21 days as you’ve requested (our competition, such as Infusionsoft, AWeber, ConvertKit, do not offer free trials at all).

With that said, I do appreciate you getting in touch and I’m sorry this last week has been a challenge. I wish you the best of luck with whichever provider you settle on.

I probably shouldn’t have been, but I have always gone out of my way to work with folks who are providing good feedback about problems that I knew we would have to solve to move forward. CNCCookbook seems to me is small enough and the problems we had seem broadly applicable enough I would’ve thought we were in that category.

In any event, we have parted company. I wish Drip all the luck, as I mentioned, I really believe in their core value proposition. Companys like CNCCookbook need affordable marketing automation.

I do have a couple of other potential solutions in mind. Heck, maybe Mailchimp will keep moving in this direction, I don’t know. I will keep you posted.

Unfortunately for me and my customers, my campaign went to 50,000 and it was wrong due to Mailchimp bugs…

I use Mailchimp as my email provider for my business, @CNCCookbook. For the past couple of weeks there’s been a terrible bug. My email RSS newsletter come out with all bad links for users that selected the Plain Text version. Every single link is bad the emails–they either go to a non-existent page or to a totally unrelated page.

At first, Mailchimp tried to convince me it was a format problem at my end because I was using the matching quotes so many editors produce. The problem is, you don’t have to look at the XML for the RSS feed very hard to see that explanation is ridiculous. Sure, those quotes are there, but the syntax of the RSS Feed makes it very obvious that those quotes are part of the article and not part of the link.

After two weeks of back and forth, they finally admitted they had a problem and that this was, “Not expected behavior.” They weren’t able to quite bring themselves to use the “B” word–BUG, but that’s clearly what it was. They also informed me they had no idea how long it would take to fix.

I waited a week, my newsletter went out this week, and I got more complaints from customers. One was particularly galling–my customer, whose is male, was addressed as “Lillian” in the newsletter. I quickly checked their profile in Mailchimp and it was not “Lillian”. In fact, there are no Lillians in the mailing list whatsoever.

Mailchimp doesn’t really respond much to all this. There is no sense of urgency. If the problem is widespread, it’s a real disaster for them. From my own perspective, the poor customer service (it’s just totally unresponsive) and the fact that this isn’t the first time I’ve had customer service issues with them have led me to start looking for a new provider.

]]>https://smoothspan.wordpress.com/2016/01/29/theres-something-terribly-wrong-with-mailchimp/feed/5Bob WarfieldMailChimp-Send-Email-CampaignIt’s Time to Tax the Robots, Not the Peoplehttps://smoothspan.wordpress.com/2015/05/20/its-time-to-tax-the-robots-not-the-people/
https://smoothspan.wordpress.com/2015/05/20/its-time-to-tax-the-robots-not-the-people/#commentsWed, 20 May 2015 17:38:59 +0000http://smoothspan.wordpress.com/?p=2802]]>I read a fascinating piece on the economic impact self-driving cars and trucks will have and it’s not a pretty sight. A quick glance at this map showing the most common job in each state makes it clear:

The most common job in each state in 2014…

You don’t have to study the map very long to conclude automating truck driving away as a way of life is going to have a profound effect on our economy. When you consider that truck drivers make an average of $40,000 a year, which is more than almost half of all tax payers, and you add in all the jobs related to the truck driving industry, it may be one of the biggest impacts we see in our lifetimes.

Can this really happen? When will it happen?

The article goes on to show that the world’s first driverless truck has already hit the road in Nevada, and was built by Mercedes Benz. They present estimates from a variety of sources that suggest somewhere between 2020 and 2030 completely autonomous trucks will begin to take over by storm. Google has demonstrated self-driving vehicles and Teslas have the capability already built in to cars already on the road.

All of the proponents of driverless vehicles are loudly trumpeting that the vehicles are safer, cheaper, and more fuel efficient. But what they’re not considering is the impact on the economy. What will all the truck drivers that lose their jobs do to earn a living? Who will benefit?

As it stands, large organizations that can afford to buy driverless vehicles will be the beneficiaries and nobody has a plan for what will happen to the truck drivers.

This looks like the third tranche of job-destroying disruption. The other two–the destruction of Retail jobs first by firms like Walmart and later by the Internet, and the Offshoring and Automation of Manufacturing jobs, are well underway. The economy is still limping in the wake of the Great Recession, and it’s tough to say we’re out of the woods except for the most dyed in the wool political supporters who want to claim victory for their side. Meanwhile, Main Street America is braced and wondering what the next big shock to the Middle Class will be.

The article argues its time to get some sort of Basic Income plan in place to provide a Safety Net. Safety Nets are fine, but I want to know how the Middle Class can do better than a Safety Net. A vibrant Middle Class does not sit at home waiting for its next Government Safety Net check to do something. A vibrant Middle Class has hopes, dreams, and upward mobility. Those are all things a Safety Net can’t cover–only Opportunity can provide hope or fulfill dreams.

It’s time to start Taxing the Robots, Not the People.

If the Robots are going to take over more and more of the economy to the detriment of the People and the benefit of those few who can own thousands of Robots, why not tax the Robots? In fact, why not look at any practice that wholesale destroys lots of jobs as being worthy of taxes to pay for programs to help those who’ve been displaced?

If we look at it that way, there are several areas to think about applying progressive taxes:

– Taxes on automation and robots

– Taxes on offshoring jobs

– Taxes on monopolies that take over markets and then use their unfair influence to gut jobs by destroying all competition

These taxes will automatically be progressive. They will help balance the playing field so that progress can still come, but there are costs that result in funds to help those displaced by progress. We don’t want to eliminate the progress, we just want to even out some of the unfairness that comes when we let progress run completely roughshod.

So far, we’ve done very much the opposite, which is part of our problem. Our system makes hiring more expensive not less. However good its intentions, Obamacare is a net job reducer because businesses have to pay for it based on how many employees they have. What if instead they paid based on how many robots, or on how many jobs they had offshored?

There’s been such a massive transfer of wealth that clearly there is money to pay for such programs. Much more than enough. While we’re at it, we should be exempting smaller businesses from such programs. It’s been well proven that Small Businesses are the engines of job creation and growth. As a nation, we’re sold on the idea of more and more progressive taxes for people, but we have left off progressive taxes for businesses.

We have a tax system that allows 43% of Americans to pay no Federal Income Tax. Why not a system that allows the smallest 43% of businesses to pay no taxes? That would dramatically level the playing field and re-ignite Small Business growth.

So, in a nutshell, what we could do to offset a continuing economic disaster for the Middle Class would be:

1. Tax Robots, Offshoring, and Monopolies so that organizations involved with these practices have the highest tax rates

2. Radically lower taxes for Small Business. Some meaningful fraction of them shouldn’t have to pay taxes at all. Perhaps not 43%, but certainly the 20% or so smallest business. Make up that lost revenue by increased taxes on larger businesses.

3. Make #1 and #2 net positive tax revenue generators to allow for new programs.

4. Put a solid Safety Net in place.

5. Stimulate the Small Business economy with what’s left. In addition to Radically Lower Small Business Taxes, we should increase the availability of Small Business Loans and we should make Education cheaper. The latter will make it easier for those whose jobs were automated away to retrain as well as ensuring an increasing pool of talented labor.

The biggest obstacle in all this thinking is that currently, the people calling the shots in terms of lobbying and poltiical contributions are precisely the ones we propose to have pay for these new programs with new taxes.

How will we ever break out of that cycle?

]]>https://smoothspan.wordpress.com/2015/05/20/its-time-to-tax-the-robots-not-the-people/feed/2Bob WarfieldJobsByStateOh Dear, the Green Pundits Don’t Understand the Cloud or Multitenancyhttps://smoothspan.wordpress.com/2015/01/16/oh-dear-the-green-pundits-dont-understand-the-cloud-or-multitenancy/
https://smoothspan.wordpress.com/2015/01/16/oh-dear-the-green-pundits-dont-understand-the-cloud-or-multitenancy/#commentsFri, 16 Jan 2015 19:46:11 +0000http://smoothspan.wordpress.com/?p=2798]]>Recently I was drawn into a discussion of how Green the Cloud is where I responded as follows:

SaaS is going to come out ahead of any reasonably calculation of carbon emissions versus on-prem. Multi-tenancy is just a lot more efficient. Look at the data centers of companies like Google, Amazon, and Facebook. Most corporates wish they could come close as they watch these companies dictate every detail right down to the exact design of servers in order to minimize their costs. As everyone agrees, most of that cost is energy.

So choose SaaS if you’re worried about carbon, and yes, it could become another axis of competition in terms of exactly which Cloud provider does it best.

Tom Raftery immediately responded:

The answer is that it depends, tbh. It depends entirely on the carbon intensity of the data centre (where it sources its energy), not the efficiency of the data centre.

If you have a data centre with a PUE of 1.2, and it is 50% coal powered (not atypical in North America, Germany, Poland, and others, for example), it will have a higher CO2 footprint than a data centre with a PUE of 3.0 powered primarily by renewables – again I have run the numbers on this and published them.

Similarly with on-prem. If I have an app that I’m running in-house, and I’m based in a country like Spain, France, Denmark, or any other country with where the electricity has a low carbon intensity; then moving to the cloud would likely increase the CO2 footprint of my application. Especially if the cloud provider is based in the US which has 45% of its electricity generated from coal.

I have a lot of problems with this kind of math–it just doesn’t tell the whole story.

First, I can’t imagine why Tom wants to be on record as saying that PUE (Power Usage Efficiency) just doesn’t matter. Sure, he has found some examples where CO2 footprint overwhelmed PUE, but to say the answer depends entirely (his word) on the sources of the data center’s energy and not on the efficiency of the data center just seems silly to me. Are there no data centers anywhere in the world at all where PUE matters? Did all the Cloud data centers with great PUE just magically get situated where the carbon footprints are lousy enough that PUE can’t matter?

I’m very skeptical that could be the case. You must consider both PUE and CO2 per Kilowatt Hour, how could we not when we’re talking per Kilowatt hour and PUE determines how many Kilowatts are required?

Here’s another one to think about. If this whole PUE/CO2 thing matters enough to affect the economics of a Cloud Vendor, we should expect them to build data centers in regions with better CO2 energy. Since they put up new data centers constantly, that’s not going to take them very long at all. Some are talking about adding solar to existing facilities as well. Now, do we want to lay odds that corporate data centers are going to be rebuilt and applications transferred as quickly for the same reasons? If you’re running corporate IT and you have a choice of selecting a Cloud Data Center with better numbers or building out a new data center yourself, which one will get you the results faster? And remember, once we are comparing Apples to Apples on CO2, those Cloud vendors’ unnaturally low PUE’s are going to start to haunt you even more as they run with fewer Kilowatt Hours.

Multitenancy Trumps all this PUE and CO2 Talk

But there’s a bigger problem here in that all data centers are not equal in another much more important way than either PUE or fuel source CO2 footprints. That problem is multitenancy. In fact, what we really want to know is CO2 emissions per seat served–that’s the solution everyone is buying. Data centers get built in order to deliver seats of some application or another, they’re a means to an end, and delivering seats is that end. The capacity they need to have, the number and type of servers, and hence the ultimate kilowatts consumed and carbon footprint produced is a function of seats. Anyone looking purely at data centers and not seats served is not seeing the whole picture. After all, if I run a corporation that has a datacenter, it’s fair to charge the carbon from that datacenter against my corporation. But if I am subscribing to some number of seats of some Cloud application, I should only be charged the carbon footprint needed to deliver just those seats. Why would I pay the carbon footprint needed to deliver seats to unrelated organizations? I wouldn’t.

Corporate data centers have been doing better over time with virtualization at being more efficient. They get a lot more seats onto a server than they used to. The days of having a separate collection of hardware for each app are gone except for the very most intensive apps. But that efficiency pales in comparison to true multitenancy. If you wonder why, read my signature article about it. I’ll run it down quickly here too.

Consider using virtual machines to run 10 apps. Through the magic of the VM, we can install 10 copies of the OS, 10 copies of the Database Server, and 10 copies of the app. Voila, we can run it all on one machine instead of 10. That’s pretty cool! Now what does Multitenancy do that the VM’s have to compete with? Let’s try an example where we’re trying to host the same software for 10 companies using VM’s. We do as mentioned and install the 10 copies of each kind of software and now we can host 10 tenants. But, with multitenancy, we install 1 copy of the OS, 1 copy of the Database, and 1 copy of the app. Then we run all 10 users in the same app. In fact, with the savings we get from not having to run all the VM’s, we can actually hose more like 1000 tenants versus 10.

But it gets better. With the Virtual Machine solution, we will need to make sure each VM has enough resources to support the peak usage loads that will be encountered. There’s not really a great way to “flex” our usage. With Multitenancy, we need to have a machine that supports the peak loads of the tenants at any moment in time on the system. We can chose to bring capacity on and off line at will, and in fact, that’s our business. For a given and very large number of seats, larger than most any single corporate application for most corporations, would we rather bet the corporation can be more efficient with on-prem software in its wholly owned data center or that the SaaS vendor will pull off far greater efficiency given that its software is purpose-built to do so? My bet is on the SaaS vendor, and not by a little, but by a lot. The SaaS vendor will beat the corporate by a minimum of 10-20x and more likely 100x on this metric. You only have to look to the financials of a SaaS company to see this. Their cost to deliver service is a very small part of their overall expenses yet most SaaS apps represent a considerable savings over the cost of On-Prem even though they carry the cost of delivering the service which the On-Prem vendor does not.